Metadata Made Easy: Develop and Use Domain‐Specific Metadata Schemes by following the dmdScheme approach

• Published in: Ecology and evolution Vol. 11; no. 14; pp. 9174 - 9181
• Main Authors: Krug, Rainer M., Petchey, Owen L.
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.07.2021; John Wiley and Sons Inc; Wiley
• Subjects: Academic Practice in Ecology and Evolution; Datasets; Dublin Core Format; Interfaces; Interoperability; Metadata; Quality assessment; Quality control; Researchers; Spreadsheets; Teaching; User interfaces; Websites
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.7764

Metadata plays an essential role in the long‐term preservation, reuse, and interoperability of data. Nevertheless, creating useful metadata can be sufficiently difficult and weakly enough incentivized that many datasets may be accompanied by little or no metadata. One key challenge is, therefore, how to make metadata creation easier and more valuable. We present a solution that involves creating domain‐specific metadata schemes that are as complex as necessary and as simple as possible. These goals are achieved by co‐development between a metadata expert and the researchers (i.e., the data creators). The final product is a bespoke metadata scheme into which researchers can enter information (and validate it) via the simplest of interfaces: a web browser application and a spreadsheet. We provide the R package dmdScheme (dmdScheme: An R package for working with domain specific MetaData schemes (Version v0.9.22), 2019) for creating a template domain‐specific scheme. We describe how to create a domain‐specific scheme from this template, including the iterative co‐development process, and the simple methods for using the scheme, and simple methods for quality assessment, improvement, and validation. The process of developing a metadata scheme following the outlined approach was successful, resulting in a metadata scheme which is used for the data generated in our research group. The validation quickly identifies forgotten metadata, as well as inconsistent metadata, therefore improving the quality of the metadata. Multiple output formats are available, including XML. Making the provision of metadata easier while also ensuring high quality must be a priority for data curation initiatives. We show how both objectives are achieved by close collaboration between metadata experts and researchers to create domain‐specific schemes. A near‐future priority is to provide methods to interface domain‐specific schemes with general metadata schemes, such as the Ecological Metadata Language, to increase interoperability. The article describes a methodology to develop, enter, and validate domain specific metadata schemes which is suitable to be used by nonmetadata specialists. The approach uses an R package which forms the backend of the processing of the metadata, uses spreadsheets to enter the metadata, and provides a server based approach to distribute and use the developed metadata schemes.